Abstract
It is argued that changes need to be made in how students are trained in contemporary computing environments. Focus is given to geophysical archaeology where knowledge of data processing is as important as understanding instrument handling in the field. While powerful and expensive commercial software programs are able to meet processing needs, it is suggested they are poorly suited for student training. In these icon-driven environments complex algorithms may be activated with a single click that requires little or no knowledge of what is actually done to the data yielding a “black box” approach to data processing. This situation contrasts with the days of pre-Windows computing when students often had to write their own code in a high-level computer language, forcing them to learn the intimate details of data processing. Such an approach is generally unacceptable today and may actually deter students from further study, yet an alternative software solution exists that can fulfill training needs. Graphically-driven modeling tools in GIS environments are available that offer diverse functionality, are easily learned, and permit most algorithms commonly applied in geophysical data processing to be constructed. Use of these tools requires complete understanding of necessary operations, their sequences and consequences. The end result is equivalent to a flowchart that shows in icon form all GIS layers input, output, and generated during intermediate steps, the various tools applied to manipulate the data, plus the full sequence of operations. In short, it is possible to teach students the art of data processing in an easy to learn and use graphical environment while imparting true knowledge of algorithms required to achieve desired outcomes. To substantiate these claims, case studies illustrate the processing of magnetic gradiometry and electrical resistance data from lateral surveys, GPR profiles in vertical investigations, and the generation of GPR time-slice maps.
Highlights
Kenneth KvammeIt is argued that changes need to be made in how students are trained in contemporary computing environments
This paper confronts a general problem in student training, but in a specific domain
This is true in archaeological remote sensing, including ground-based geophysics, with the rise of sub-meter resolution satellites, LiDAR and drone surveys, vehicle-driven carts holding arrays of geophysical sensors, and the like, all coming to fruition within the past decade or so
Summary
It is argued that changes need to be made in how students are trained in contemporary computing environments. While powerful and expensive commercial software programs are able to meet processing needs, it is suggested they are poorly suited for student training In these icon-driven environments complex algorithms may be activated with a single click that requires little or no knowledge of what is done to the data yielding a “black box” approach to data processing. This situation contrasts with the days of pre-Windows computing when students often had to write their own code in a high-level computer language, forcing them to learn the intimate details of data processing.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
